nep-ets New Economics Papers
on Econometric Time Series
Issue of 2006‒03‒11
five papers chosen by
Yong Yin
SUNY at Buffalo

  1. Cointegration and the stabilizing role of exchange rates By Alexius, Annika; Post, Erik
  2. Forecasting interest rates: A Comparative assessment of some second generation non-linear model By Dilip M. Nachane; Jose G. Clavel
  3. Equity Return and Short-Term Interest Rate Volatility: Level Effects and Asymmetric Dynamics By Sandy Suardi; O.T.Henry; N. Olekalns
  4. Common Functional Implied Volatility Analysis By Michal Benko; Wolfgang Härdle
  5. The Power of Bootstrap and Asymptotic Tests By Russell Davidson; James MacKinnon

  1. By: Alexius, Annika (Department of Economics); Post, Erik (Department of Economics)
    Abstract: We show that empirical results concerning the behavior of floating exchange rates differ between otherwise identical cointegrated and non-cointegrated VAR models. In particular, virtually all ten-year movements in nominal exchange rates are due to fundamental supply and demand shocks when long run equilibrium relationships between the levels of the variables are included in the empirical specification. Another major difference between the models with the opposite implication for the shock creation versus shock absorption debate is that non-fundamental exchange rate shocks have much larger effects on output and inflation in the cointegrated models. Finally, impulse response functions in the first difference specification die out within a year whereas adjustment to long run equilibrium continues for up to ten years in the cointegrated models. Hence a correct specification of the long-run equilibrium dynamics of exchange rates is essential for capturing also short-run behavior of exchange rates.
    Keywords: Exchange rates; asymmetric shocks; structural VAR; cointegration
    JEL: C32 F31
    Date: 2006–02
  2. By: Dilip M. Nachane (Indira Gandhi Institute of Development Research); Jose G. Clavel (Universidad de Murcia)
    Abstract: Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis-vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.
    Keywords: Interest rates, wavelets, mixed spectra, non-linear ARMA, Kalman filter, GARCH, Forecast encompassing
    Date: 2005
  3. By: Sandy Suardi (MRG - School of Economics, The University of Queensland); O.T.Henry; N. Olekalns
    Abstract: Evidence suggests that short-term interest rate volatility peaks with the level of short rates, while equity volatility responds asymmetrically to positive and negative shocks. We present an LM based test that distinguishes between level effects and asymmetry in volatility which is robust to the presence of unidentified nuisance parameters under the null. There is strong evidence of a level effect and asymmetric response in the relationship between S&P 500 Index returns and 3-month US Treasury Bills. The conditional covariance depends on the level of the short rate which has implications for hedging equity returns against short term interest rate movements.
  4. By: Michal Benko; Wolfgang Härdle
    Abstract: Trading, hedging and risk analysis of complex option portfolios depend on accurate pricing models. The modelling of implied volatilities (IV) plays an important role, since volatility is the crucial parameter in the Black-Scholes (BS) pricing formula. It is well known from empirical studies that the volatilities implied by observed market prices exhibit patterns known as volatility smiles or smirks that contradict the assumption of constant volatility in the BS pricing model. On the other hand, the IV is a function of two parameters: the strike price and the time to maturity and it is desirable in practice to reduce the dimension of this object and characterize the IV surface through a small number of factors. Clearly, a dimension reduced pricing-model that should reflect the dynamics of the IV surface needs to contain factors and factor loadings that characterize the IV surface itself and their movements across time.
    Keywords: implied volatility, Black-Scholes, option portfolio, pricing
    JEL: C13 G19
    Date: 2005–03
  5. By: Russell Davidson (McGill University); James MacKinnon (Queen's University)
    Abstract: We introduce the concept of the bootstrap discrepancy, which measures the difference in rejection probabilities between a bootstrap test based on a given test statistic and that of a (usually infeasible) test based on the true distribution of the statistic. We show that the bootstrap discrepancy is of the same order of magnitude under the null hypothesis and under non-null processes described by a Pitman drift. However, complications arise in the measurement of power. If the test statistic is not an exact pivot, critical values depend on which data-generating process (DGP) is used to determine the distribution under the null hypothesis. We propose as the proper choice the DGP which minimizes the bootstrap discrepancy. We also show that, under an asymptotic independence condition, the power of both bootstrap and asymptotic tests can be estimated cheaply by simulation. The theory of the paper and the proposed simulation method are illustrated by Monte Carlo experiments using the logit model.
    Keywords: bootstrap test, bootstrap discrepancy, Pitman drift, drifting DGP, Monte Carlo, test power
    JEL: C12 C15
    Date: 2004–07

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